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            <td width="10%" class="headerItem">Current view:</td>
            <td width="35%" class="headerValue"><a href="../../../index.html">top level</a> - <a href="index.html">src/caffe/layers</a> - reduction_layer.cpp<span style="font-size: 80%;"> (source / <a href="reduction_layer.cpp.func-sort-c.html">functions</a>)</span></td>
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            <td width="10%" class="headerCovTableHead">Hit</td>
            <td width="10%" class="headerCovTableHead">Total</td>
            <td width="15%" class="headerCovTableHead">Coverage</td>
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            <td class="headerItem">Test:</td>
            <td class="headerValue">code analysis</td>
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            <td class="headerItem">Lines:</td>
            <td class="headerCovTableEntry">2</td>
            <td class="headerCovTableEntry">63</td>
            <td class="headerCovTableEntryLo">3.2 %</td>
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            <td class="headerItem">Date:</td>
            <td class="headerValue">2020-09-11 22:25:26</td>
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            <td class="headerItem">Functions:</td>
            <td class="headerCovTableEntry">2</td>
            <td class="headerCovTableEntry">16</td>
            <td class="headerCovTableEntryLo">12.5 %</td>
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            <td class="headerValueLeg">            Lines:
            <span class="coverLegendCov">hit</span>
            <span class="coverLegendNoCov">not hit</span>
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<pre class="sourceHeading">          Line data    Source code</pre>
<pre class="source">
<a name="1"><span class="lineNum">       1 </span>            : #include &lt;vector&gt;</a>
<span class="lineNum">       2 </span>            : 
<span class="lineNum">       3 </span>            : #include &quot;caffe/layers/reduction_layer.hpp&quot;
<span class="lineNum">       4 </span>            : #include &quot;caffe/util/math_functions.hpp&quot;
<span class="lineNum">       5 </span>            : 
<span class="lineNum">       6 </span>            : namespace caffe {
<a name="7"><span class="lineNum">       7 </span>            : </a>
<span class="lineNum">       8 </span>            : template &lt;typename Dtype&gt;
<span class="lineNum">       9 </span><span class="lineNoCov">          0 : void ReductionLayer&lt;Dtype&gt;::LayerSetUp(const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; bottom,</span>
<span class="lineNum">      10 </span>            :       const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; top) {
<span class="lineNum">      11 </span><span class="lineNoCov">          0 :   op_ = this-&gt;layer_param_.reduction_param().operation();</span>
<span class="lineNum">      12 </span><span class="lineNoCov">          0 : }</span>
<span class="lineNum">      13 </span>            : 
<span class="lineNum">      14 </span>            : template &lt;typename Dtype&gt;
<span class="lineNum">      15 </span><span class="lineNoCov">          0 : void ReductionLayer&lt;Dtype&gt;::Reshape(const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; bottom,</span>
<span class="lineNum">      16 </span>            :       const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; top) {
<span class="lineNum">      17 </span><span class="lineNoCov">          0 :   axis_ = bottom[0]-&gt;CanonicalAxisIndex(</span>
<span class="lineNum">      18 </span>            :       this-&gt;layer_param_.reduction_param().axis());
<span class="lineNum">      19 </span>            :   // In the output, we'll keep all axes up to the reduction axis, but
<span class="lineNum">      20 </span>            :   // throw away any after that.
<span class="lineNum">      21 </span>            :   // Note: currently reducing along non-tail axes is not supported; otherwise,
<span class="lineNum">      22 </span>            :   // we'd need to also copy any axes following an &quot;end_axis&quot;.
<span class="lineNum">      23 </span>            :   vector&lt;int&gt; top_shape(bottom[0]-&gt;shape().begin(),
<span class="lineNum">      24 </span><span class="lineNoCov">          0 :                         bottom[0]-&gt;shape().begin() + axis_);</span>
<span class="lineNum">      25 </span><span class="lineNoCov">          0 :   top[0]-&gt;Reshape(top_shape);</span>
<span class="lineNum">      26 </span><span class="lineNoCov">          0 :   num_ = bottom[0]-&gt;count(0, axis_);</span>
<span class="lineNum">      27 </span><span class="lineNoCov">          0 :   dim_ = bottom[0]-&gt;count(axis_);</span>
<span class="lineNum">      28 </span><span class="lineNoCov">          0 :   CHECK_EQ(num_, top[0]-&gt;count());</span>
<span class="lineNum">      29 </span><span class="lineNoCov">          0 :   if (op_ == ReductionParameter_ReductionOp_SUM ||</span>
<span class="lineNum">      30 </span>            :       op_ == ReductionParameter_ReductionOp_MEAN) {
<span class="lineNum">      31 </span><span class="lineNoCov">          0 :     vector&lt;int&gt; sum_mult_shape(1, dim_);</span>
<span class="lineNum">      32 </span><span class="lineNoCov">          0 :     sum_multiplier_.Reshape(sum_mult_shape);</span>
<span class="lineNum">      33 </span><span class="lineNoCov">          0 :     caffe_set(dim_, Dtype(1), sum_multiplier_.mutable_cpu_data());</span>
<span class="lineNum">      34 </span>            :   }
<span class="lineNum">      35 </span><span class="lineNoCov">          0 :   coeff_ = this-&gt;layer_param().reduction_param().coeff();</span>
<span class="lineNum">      36 </span><span class="lineNoCov">          0 :   if (op_ == ReductionParameter_ReductionOp_MEAN) {</span>
<span class="lineNum">      37 </span><span class="lineNoCov">          0 :     coeff_ /= dim_;</span>
<span class="lineNum">      38 </span>            :   }
<span class="lineNum">      39 </span><span class="lineNoCov">          0 : }</span>
<a name="40"><span class="lineNum">      40 </span>            : </a>
<span class="lineNum">      41 </span>            : template &lt;typename Dtype&gt;
<span class="lineNum">      42 </span><span class="lineNoCov">          0 : void ReductionLayer&lt;Dtype&gt;::Forward_cpu(</span>
<span class="lineNum">      43 </span>            :     const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; bottom, const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; top) {
<span class="lineNum">      44 </span><span class="lineNoCov">          0 :   const Dtype* bottom_data = bottom[0]-&gt;cpu_data();</span>
<span class="lineNum">      45 </span>            :   const Dtype* mult_data = NULL;
<span class="lineNum">      46 </span><span class="lineNoCov">          0 :   if (sum_multiplier_.count() &gt; 0) {</span>
<span class="lineNum">      47 </span><span class="lineNoCov">          0 :     mult_data = sum_multiplier_.cpu_data();</span>
<span class="lineNum">      48 </span>            :   }
<span class="lineNum">      49 </span><span class="lineNoCov">          0 :   Dtype* top_data = top[0]-&gt;mutable_cpu_data();</span>
<span class="lineNum">      50 </span><span class="lineNoCov">          0 :   for (int i = 0; i &lt; num_; ++i) {</span>
<span class="lineNum">      51 </span><span class="lineNoCov">          0 :     switch (op_) {</span>
<span class="lineNum">      52 </span>            :     case ReductionParameter_ReductionOp_SUM:
<span class="lineNum">      53 </span>            :     case ReductionParameter_ReductionOp_MEAN:
<span class="lineNum">      54 </span><span class="lineNoCov">          0 :       *top_data = caffe_cpu_dot(dim_, mult_data, bottom_data);</span>
<span class="lineNum">      55 </span><span class="lineNoCov">          0 :       break;</span>
<span class="lineNum">      56 </span>            :     case ReductionParameter_ReductionOp_ASUM:
<span class="lineNum">      57 </span><span class="lineNoCov">          0 :       *top_data = caffe_cpu_asum(dim_, bottom_data);</span>
<span class="lineNum">      58 </span><span class="lineNoCov">          0 :       break;</span>
<span class="lineNum">      59 </span>            :     case ReductionParameter_ReductionOp_SUMSQ:
<span class="lineNum">      60 </span><span class="lineNoCov">          0 :       *top_data = caffe_cpu_dot(dim_, bottom_data, bottom_data);</span>
<span class="lineNum">      61 </span><span class="lineNoCov">          0 :       break;</span>
<span class="lineNum">      62 </span>            :     default:
<span class="lineNum">      63 </span><span class="lineNoCov">          0 :       LOG(FATAL) &lt;&lt; &quot;Unknown reduction op: &quot;</span>
<span class="lineNum">      64 </span>            :           &lt;&lt; ReductionParameter_ReductionOp_Name(op_);
<span class="lineNum">      65 </span>            :     }
<span class="lineNum">      66 </span><span class="lineNoCov">          0 :     bottom_data += dim_;</span>
<span class="lineNum">      67 </span><span class="lineNoCov">          0 :     ++top_data;</span>
<span class="lineNum">      68 </span>            :   }
<span class="lineNum">      69 </span><span class="lineNoCov">          0 :   if (coeff_ != Dtype(1)) {</span>
<span class="lineNum">      70 </span>            :     // Reset the top_data pointer.
<span class="lineNum">      71 </span><span class="lineNoCov">          0 :     top_data = top[0]-&gt;mutable_cpu_data();</span>
<span class="lineNum">      72 </span><span class="lineNoCov">          0 :     caffe_scal(num_, coeff_, top_data);</span>
<span class="lineNum">      73 </span>            :   }
<span class="lineNum">      74 </span><span class="lineNoCov">          0 : }</span>
<a name="75"><span class="lineNum">      75 </span>            : </a>
<span class="lineNum">      76 </span>            : template &lt;typename Dtype&gt;
<span class="lineNum">      77 </span><span class="lineNoCov">          0 : void ReductionLayer&lt;Dtype&gt;::Backward_cpu(const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; top,</span>
<span class="lineNum">      78 </span>            :     const vector&lt;bool&gt;&amp; propagate_down, const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; bottom) {
<span class="lineNum">      79 </span><span class="lineNoCov">          0 :   if (!propagate_down[0]) { return; }</span>
<span class="lineNum">      80 </span>            :   // Get bottom_data, if needed.
<span class="lineNum">      81 </span>            :   const Dtype* bottom_data = NULL;
<span class="lineNum">      82 </span><span class="lineNoCov">          0 :   switch (op_) {</span>
<span class="lineNum">      83 </span>            :   // Operations that don't need bottom_data
<span class="lineNum">      84 </span>            :   case ReductionParameter_ReductionOp_SUM:
<span class="lineNum">      85 </span>            :   case ReductionParameter_ReductionOp_MEAN:
<span class="lineNum">      86 </span>            :     break;
<span class="lineNum">      87 </span>            :   // Operations that need bottom_data
<span class="lineNum">      88 </span>            :   case ReductionParameter_ReductionOp_ASUM:
<span class="lineNum">      89 </span>            :   case ReductionParameter_ReductionOp_SUMSQ:
<span class="lineNum">      90 </span><span class="lineNoCov">          0 :     bottom_data = bottom[0]-&gt;cpu_data();</span>
<span class="lineNum">      91 </span><span class="lineNoCov">          0 :     break;</span>
<span class="lineNum">      92 </span>            :   default:
<span class="lineNum">      93 </span><span class="lineNoCov">          0 :     LOG(FATAL) &lt;&lt; &quot;Unknown reduction op: &quot;</span>
<span class="lineNum">      94 </span>            :         &lt;&lt; ReductionParameter_ReductionOp_Name(op_);
<span class="lineNum">      95 </span>            :   }
<span class="lineNum">      96 </span><span class="lineNoCov">          0 :   const Dtype* top_diff = top[0]-&gt;cpu_diff();</span>
<span class="lineNum">      97 </span><span class="lineNoCov">          0 :   Dtype* bottom_diff = bottom[0]-&gt;mutable_cpu_diff();</span>
<span class="lineNum">      98 </span><span class="lineNoCov">          0 :   for (int i = 0; i &lt; num_; ++i) {</span>
<span class="lineNum">      99 </span><span class="lineNoCov">          0 :     const Dtype bottom_coeff = (*top_diff) * coeff_;</span>
<span class="lineNum">     100 </span><span class="lineNoCov">          0 :     switch (op_) {</span>
<span class="lineNum">     101 </span>            :     case ReductionParameter_ReductionOp_SUM:
<span class="lineNum">     102 </span>            :     case ReductionParameter_ReductionOp_MEAN:
<span class="lineNum">     103 </span><span class="lineNoCov">          0 :       caffe_set(dim_, bottom_coeff, bottom_diff);</span>
<span class="lineNum">     104 </span><span class="lineNoCov">          0 :       break;</span>
<span class="lineNum">     105 </span>            :     case ReductionParameter_ReductionOp_ASUM:
<span class="lineNum">     106 </span><span class="lineNoCov">          0 :       caffe_cpu_sign(dim_, bottom_data, bottom_diff);</span>
<span class="lineNum">     107 </span><span class="lineNoCov">          0 :       caffe_scal(dim_, bottom_coeff, bottom_diff);</span>
<span class="lineNum">     108 </span><span class="lineNoCov">          0 :       break;</span>
<span class="lineNum">     109 </span>            :     case ReductionParameter_ReductionOp_SUMSQ:
<span class="lineNum">     110 </span><span class="lineNoCov">          0 :       caffe_cpu_scale(dim_, 2 * bottom_coeff, bottom_data, bottom_diff);</span>
<span class="lineNum">     111 </span><span class="lineNoCov">          0 :       break;</span>
<span class="lineNum">     112 </span>            :     default:
<span class="lineNum">     113 </span><span class="lineNoCov">          0 :       LOG(FATAL) &lt;&lt; &quot;Unknown reduction op: &quot;</span>
<span class="lineNum">     114 </span>            :           &lt;&lt; ReductionParameter_ReductionOp_Name(op_);
<span class="lineNum">     115 </span>            :     }
<span class="lineNum">     116 </span><span class="lineNoCov">          0 :     bottom_data += dim_;</span>
<span class="lineNum">     117 </span><span class="lineNoCov">          0 :     bottom_diff += dim_;</span>
<span class="lineNum">     118 </span><span class="lineNoCov">          0 :     ++top_diff;</span>
<span class="lineNum">     119 </span>            :   }
<span class="lineNum">     120 </span>            : }
<a name="121"><span class="lineNum">     121 </span>            : </a>
<span class="lineNum">     122 </span>            : #ifdef CPU_ONLY
<span class="lineNum">     123 </span><span class="lineNoCov">          0 : STUB_GPU(ReductionLayer);</span>
<span class="lineNum">     124 </span>            : #endif
<span class="lineNum">     125 </span>            : 
<span class="lineNum">     126 </span>            : INSTANTIATE_CLASS(ReductionLayer);
<a name="127"><span class="lineNum">     127 </span><span class="lineCov">          3 : REGISTER_LAYER_CLASS(Reduction);</span></a>
<span class="lineNum">     128 </span>            : 
<span class="lineNum">     129 </span><span class="lineCov">          3 : }  // namespace caffe</span>
</pre>
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